Voting for pro-climate parties and candidates in response to extreme flooding experience

Søren Damsbo-Svendsen
soerendamsbo.github.io

December 2, 2022

Background

Background: extreme weather experience → behavior

RQ: How does climate-related extreme weather experience affect pro-climate voting?

  • Ample evidence that extreme weather experience affect climate change perceptions and attitudes
  • But limited (and mixed) evidence that weather experiences affect actual behavior:
    1. environmental behavior: it does not increase private energy saving, recycling, etc. (e.g. Rüttenauer 2021)
    2. information/communication behavior: it can increase Twitter climate discussion, community dicussion, and web searches (e.g. Boudet et al. 2019; Osberghaus & Demski 2019; Sisco et al. 2017)
    3. How about more collective, political behavior?
      • Pro-climate voting!

Background: extreme weather experience → behavior

RQ: How does climate-related extreme weather experience affect pro-climate voting?

Pro-climate voting:

  • “a sizeable effect for pro-climate voting [20 %-points] after experiencing a flood” (Baccini & Leemann 2021)
  • Californian wildfires increase support for costly, pro-environment policies by 5-6 %-points (Hazlett & Mildenberger 2020)
  • Studies of retrospective voting and natural disasters sometimes show electoral rewards for (relatively) pro-climate parties (e.g. Gasper & Reeves 2011; Bechtel & Hainmueller 2011)
  • Some null findings (e.g. Hilbig & Riaz, 2022; Melville-Rea 2022)

Severe northern European storm surge in December 2013

Northern Europe on
December 5 2013

European Environment Agency

Lynæs Bådelaug

rktic

Vikingeskibsmuseet

Jeanne & John Bollerup-Jensen

Storm surge in Denmark, December 2013

  • A rarely harmful and costly weather event → “Hurricane Sandy-equivalent”
  • Data: detailed and complete geocoded storm surge insurance cases from the Danish Storm Council
  • N = 2,924

Study I: how the vote share of pro-climate parties increases after the flood

Study I: voting for pro-climate parties

  • Level of analysis: 1,386 polling districts

  • Context: Danish parliamentary elections 1998-2019 (focus on 2011-2015)

  • Outcome: district vote share for pro-climate parties

    • left-green bloc w/ strong issue ownership

  • Matched with district flooding based on 3 treatment definitions (all binary):

    1. Storm surge damages (USD) above average
    2. 1+ cases of rehousing cases
    3. 1+ total flooding cases

  • Difference-in-differences (DID) design

Study I: DID results - main


→ flooding effect on pro-climate voting approx. 2-4 %-points

Study I: DID robustness - propensity-score matching


  • Following Abadie (2005)
  • Matching on relatively unbalanced covariates (possible confounders):
    • ln(polling district area), ln(distance to the water), ln(historical average turnout), academic education (%), primary education (%), ln(median income), ln(total wealth), single-family homes (%)
  • DID estimate (damages): 2.06 (bootstrapped 95% CI: [1.11, 3.02])
  • No placebo effects


→ flooding effect robust to covariate matching

Study I: DID results - flooding intensity


→ flooding effect tends to grow with flooding intensity

Study II: how voters reward pro-climate candidates with higher election chances after the flood

Study II: voting for pro-climate candidates


  • Level of analysis: 9,554 election candidates

  • Context: Danish local elections 2009-2017 (focus on 2013-2017)

  • Outcome: elected or not (binary)

  • Data: candidate survey w/ climate-related policy responses from 73% of candidates

  • Pro-climate candidate (binary): climate as key priority or climate score above 4/5

  • Treatment: high economic damage in municipality where candidate is running

  • Triple differences (DIDID) design

Study II: expectation


Pro-climate candidates within each party (%)

  1. If voters engage in pro-climate voting,
  2. the gap in election chances of pro-climate candidates versus non-climate candidates
  3. should increase in heavily flooded communities (because of the flood)
  4. → positive DIDID

Study II: DIDID results

Study II: DIDID results


  • DIDID, all parties: approx. 7.8 %-points

  • DIDID, pro-climate parties: approx. 14.2 %-points

  • → pro-climate candidates benefit electorally in post-flooding elections

Study II: DIDID placebo test


  • Clear DIDID effects in real test (>1 rehousing cases)
  • No DIDID effects in placebo test
  • And also no DIDID for other candidate features: incumbent and pro-welfare

Conclusions

Conclusions 1/2


RQ: How does climate-related extreme weather experience affect pro-climate voting?

  • Case: 2013 storm surge and surrounding Danish elections
  • Detailed insurance data → local flooding exposure
  • Twofold empirical study:

Conclusions 2/2


RQ: How does climate-related extreme weather experience affect pro-climate voting?

  • Pro-climate parties (left-green bloc) gain around 2 %-points (or more) in flooded areas
  • Pro-climate candidates see their election chances increase by 7.8 %-points vs. non-climate candidates
    • (more for candidates in the pro-climate parties)
  • Extreme weather experiences can have significant, long-lasting effects on actual behavior → pro-climate voting
  • Voters connect weather events to climate policy (at least implicitly) and make voting decisions on this basis

Thank you!

→ sdas@ifs.ku.dk

Marco Faria

Supplementary material

Environmental issue ownership

Study I: pretreatment balance

→ flooded and unflooded areas are fairly well-balanced on most covariates

Study I: DID robustness - event study plots (matched)

→ post-flood effect (green) and no placebo effects in the matching-event study plot

Study I: DID robustness - event study plots (raw)

→ some imbalances; 2011 appears to be the odd one

Study I: DID robustness - alternative baseline


→ with alternative baseline (2007) still flooding effect of at least 1.5 %-points